92 research outputs found
Portable machine welding head automatically controls arc
Portable weld tool makes weld repairs out-of-station and on the side opposite the original weld. It provides full automatic control of the arc voltage, current, wire feed, and electrode travel speed in all welding attitudes. The device is readily adaptable to commercially available straight polarity dc weld packs
Genomic Variation Among Populations of Threatened Coral: Acropora cervicornis
Background: Acropora cervicornis, a threatened, keystone reef-building coral has undergone severe declines (\u3e90 %) throughout the Caribbean. These declines could reduce genetic variation and thus hamper the species’ ability to adapt. Active restoration strategies are a common conservation approach to mitigate species\u27 declines and require genetic data on surviving populations to efficiently respond to declines while maintaining the genetic diversity needed to adapt to changing conditions. To evaluate active restoration strategies for the staghorn coral, the genetic diversity of A. cervicornis within and among populations was assessed in 77 individuals collected from 68 locations along the Florida Reef Tract (FRT) and in the Dominican Republic.
Results: Genotyping by Sequencing (GBS) identified 4,764 single nucleotide polymorphisms (SNPs). Pairwise nucleotide differences (π) within a population are large (~37 %) and similar to π across all individuals. This high level of genetic diversity along the FRT is similar to the diversity within a small, isolated reef. Much of the genetic diversity (\u3e90 %) exists within a population, yet GBS analysis shows significant variation along the FRT, including 300 SNPs with significant FST values and significant divergence relative to distance. There are also significant differences in SNP allele frequencies over small spatial scales, exemplified by the large FST values among corals collected within Miami-Dade county.
Conclusions: Large standing diversity was found within each population even after recent declines in abundance, including significant, potentially adaptive divergence over short distances. The data here inform conservation and management actions by uncovering population structure and high levels of diversity maintained within coral collections among sites previously shown to have little genetic divergence. More broadly, this approach demonstrates the power of GBS to resolve differences among individuals and identify subtle genetic structure, informing conservation goals with evolutionary implications
The landscape of extreme genomic variation in the highly adaptable Atlantic killifish
© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Genome Biology and Evolution 9 (2017): 659-676, doi:10.1093/gbe/evx023.Understanding and predicting the fate of populations in changing environments require knowledge about the mechanisms that support phenotypic plasticity and the adaptive value and evolutionary fate of genetic variation within populations. Atlantic killifish (Fundulus heteroclitus) exhibit extensive phenotypic plasticity that supports large population sizes in highly fluctuating estuarine environments. Populations have also evolved diverse local adaptations. To yield insights into the genomic variation that supports their adaptability, we sequenced a reference genome and 48 additional whole genomes from a wild population. Evolution of genes associated with cell cycle regulation and apoptosis is accelerated along the killifish lineage, which is likely tied to adaptations for life in highly variable estuarine environments. Genome-wide standing genetic variation, including nucleotide diversity and copy number variation, is extremely high. The highest diversity genes are those associated with immune function and olfaction, whereas genes under greatest evolutionary constraint are those associated with neurological, developmental, and cytoskeletal functions. Reduced genetic variation is detected for tight junction proteins, which in killifish regulate paracellular permeability that supports their extreme physiological flexibility. Low-diversity genes engage in more regulatory interactions than high-diversity genes, consistent with the influence of pleiotropic constraint on molecular evolution. High genetic variation is crucial for continued persistence of species given the pace of contemporary environmental change. Killifish populations harbor among the highest levels of nucleotide diversity yet reported for a vertebrate species, and thus may serve as a useful model system for studying evolutionary potential in variable and changing environments.This work was primarily supported by a grant from the National Science Foundation (collaborative research grants DEB-1265282, DEB-1120512, DEB-1120013, DEB-1120263, DEB-1120333, DEB-1120398 to J.K.C., D.L.C., M.E.H., S.I.K., M.F.O., J.R.S., W.W., and A.W.). Further support was provided by the National Institute of Environmental Health Sciences (1R01ES021934-01 to A.W., P42ES7373 to T.H.H., P42ES007381 to M.E.H., and R01ES019324 to J.R.S.), the National Institute of General Medical Sciences (P20GM103423 and P20GM104318 to B.L.K.), and the National Science Foundation (DBI-0640462 and XSEDE-MCB100147 to D.G.)
Gene Expression Variability within and between Human Populations and Implications toward Disease Susceptibility
Variations in gene expression level might lead to phenotypic diversity across individuals or populations. Although many human genes are found to have differential mRNA levels between populations, the extent of gene expression that could vary within and between populations largely remains elusive. To investigate the dynamic range of gene expression, we analyzed the expression variability of ∼18, 000 human genes across individuals within HapMap populations. Although ∼20% of human genes show differentiated mRNA levels between populations, our results show that expression variability of most human genes in one population is not significantly deviant from another population, except for a small fraction that do show substantially higher expression variability in a particular population. By associating expression variability with sequence polymorphism, intriguingly, we found SNPs in the untranslated regions (5′ and 3′UTRs) of these variable genes show consistently elevated population heterozygosity. We performed differential expression analysis on a genome-wide scale, and found substantially reduced expression variability for a large number of genes, prohibiting them from being differentially expressed between populations. Functional analysis revealed that genes with the greatest within-population expression variability are significantly enriched for chemokine signaling in HIV-1 infection, and for HIV-interacting proteins that control viral entry, replication, and propagation. This observation combined with the finding that known human HIV host factors show substantially elevated expression variability, collectively suggest that gene expression variability might explain differential HIV susceptibility across individuals
The genomic landscape of rapid repeated evolutionary adaptation to toxic pollution in wild fish
Author Posting. © The Author(s), 2016. This is the author's version of the work. It is posted here under a nonexclusive, irrevocable, paid-up, worldwide license granted to WHOI. It is made available for personal use, not for redistribution. The definitive version was published in Science 354 (2016): 1305-1308, doi:10.1126/science.aah4993.Atlantic killifish populations have rapidly adapted to normally lethal levels of pollution in four
urban estuaries. Through analysis of 384 whole killifish genome sequences and comparative
transcriptomics in four pairs of sensitive and tolerant populations, we identify the aryl
hydrocarbon receptor-based signaling pathway as a shared target of selection. This suggests
evolutionary constraint on adaptive solutions to complex toxicant mixtures at each site. However,
distinct molecular variants apparently contribute to adaptive pathway modification among
tolerant populations. Selection also targets other toxicity-mediating genes, and genes of
connected signaling pathways, indicating complex tolerance phenotypes and potentially
compensatory adaptations. Molecular changes are consistent with selection on standing genetic
variation. In killifish high nucleotide diversity has likely been a crucial substrate for selective
sweeps to propel rapid adaptation.Primary support was from the United States
National Science Foundation (collaborative research grants DEB-1265282, DEB-1120512, DEB-
1120013, DEB-1120263, DEB-1120333, DEB-1120398 to JKC, DLC, MEH, SIK, MFO, JRS,
WW, and AW). Further support was provided by the National Institutes of Environmental Health
Sciences (1R01ES021934-01 to AW; P42ES007381 to MEH; R01ES019324 to JRS), and the
National Science Foundation (OCE-1314567 to AW). BC was supported by the Postdoctoral
Research Program at the US EPA administered by the Oak Ridge Institute for Science and
Education (Agreement DW92429801)
Moving toward a system genetics view of disease
Testing hundreds of thousands of DNA markers in human, mouse, and other species for association to complex traits like disease is now a reality. However, information on how variations in DNA impact complex physiologic processes flows through transcriptional and other molecular networks. In other words, DNA variations impact complex diseases through the perturbations they cause to transcriptional and other biological networks, and these molecular phenotypes are intermediate to clinically defined disease. Because it is also now possible to monitor transcript levels in a comprehensive fashion, integrating DNA variation, transcription, and phenotypic data has the potential to enhance identification of the associations between DNA variation and diseases like obesity and diabetes, as well as characterize those parts of the molecular networks that drive these diseases. Toward that end, we review methods for integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data to infer causal relationships among gene expression traits and between expression and clinical traits. We further describe methods to integrate these data in a more comprehensive manner by constructing coexpression gene networks that leverage pairwise gene interaction data to represent more general relationships. To infer gene networks that capture causal information, we describe a Bayesian algorithm that further integrates eQTLs, expression, and clinical phenotype data to reconstruct whole-gene networks capable of representing causal relationships among genes and traits in the network. These emerging network approaches, aimed at processing high-dimensional biological data by integrating data from multiple sources, represent some of the first steps in statistical genetics to identify multiple genetic perturbations that alter the states of molecular networks and that in turn push systems into disease states. Evolving statistical procedures that operate on networks will be critical to extracting information related to complex phenotypes like disease, as research goes beyond a single-gene focus. The early successes achieved with the methods described herein suggest that these more integrative genomics approaches to dissecting disease traits will significantly enhance the identification of key drivers of disease beyond what could be achieved by genetic association studies alone
Gene expression throughout a vertebrate's embryogenesis
Abstract Background Describing the patterns of gene expression during embryonic development has broadened our understanding of the processes and patterns that define morphogenesis. Yet gene expression patterns have not been described throughout vertebrate embryogenesis. This study presents statistical analyses of gene expression during all 40 developmental stages in the teleost Fundulus heteroclitus using four biological replicates per stage. Results Patterns of gene expression for 7,000 genes appear to be important as they recapitulate developmental timing. Among the 45% of genes with significant expression differences between pairs of temporally adjacent stages, significant differences in gene expression vary from as few as five to more than 660. Five adjacent stages have disproportionately more significant changes in gene expression (> 200 genes) relative to other stages: four to eight and eight to sixteen cell stages, onset of circulation, pre and post-hatch, and during complete yolk absorption. The fewest differences among adjacent stages occur during gastrulation. Yet, at stage 16, (pre-mid-gastrulation) the largest number of genes has peak expression. This stage has an over representation of genes in oxidative respiration and protein expression (ribosomes, translational genes and proteases). Unexpectedly, among all ribosomal genes, both strong positive and negative correlations occur. Similar correlated patterns of expression occur among all significant genes. Conclusions These data provide statistical support for the temporal dynamics of developmental gene expression during all stages of vertebrate development
Location-Specific Responses to Thermal Stress in Larvae of the Reef-Building Coral Montastraea faveolata
The potential to adapt to a changing climate depends in part upon the standing genetic variation present in wild populations. In corals, the dispersive larval phase is particularly vulnerable to the effects of environmental stress. Larval survival and response to stress during dispersal and settlement will play a key role in the persistence of coral populations.To test the hypothesis that larval transcription profiles reflect location-specific responses to thermal stress, symbiont-free gametes from three to four colonies of the scleractinian coral Montastraea faveolata were collected from Florida and Mexico, fertilized, and raised under mean and elevated (up 1 to 2 degrees C above summer mean) temperatures. These locations have been shown to exchange larvae frequently enough to prevent significant differentiation of neutral loci. Differences among 1,310 unigenes were simultaneously characterized using custom cDNA microarrays, allowing investigation of gene expression patterns among larvae generated from wild populations under stress. Results show both conserved and location-specific variation in key processes including apoptosis, cell structuring, adhesion and development, energy and protein metabolism, and response to stress, in embryos of a reef-building coral.These results provide first insights into location-specific variation in gene expression in the face of gene flow, and support the hypothesis that coral host genomes may house adaptive potential needed to deal with changing environmental conditions
A Population Proportion approach for ranking differentially expressed genes
<p>Abstract</p> <p>Background</p> <p>DNA microarrays are used to investigate differences in gene expression between two or more classes of samples. Most currently used approaches compare mean expression levels between classes and are not geared to find genes whose expression is significantly different in only a subset of samples in a class. However, biological variability can lead to situations where key genes are differentially expressed in only a subset of samples. To facilitate the identification of such genes, a new method is reported.</p> <p>Methods</p> <p>The key difference between the Population Proportion Ranking Method (PPRM) presented here and almost all other methods currently used is in the quantification of variability. PPRM quantifies variability in terms of inter-sample ratios and can be used to calculate the relative merit of differentially expressed genes with a specified difference in expression level between at least some samples in the two classes, which at the same time have lower than a specified variability within each class.</p> <p>Results</p> <p>PPRM is tested on simulated data and on three publicly available cancer data sets. It is compared to the t test, PPST, COPA, OS, ORT and MOST using the simulated data. Under the conditions tested, it performs as well or better than the other methods tested under low intra-class variability and better than t test, PPST, COPA and OS when a gene is differentially expressed in only a subset of samples. It performs better than ORT and MOST in recognizing non differentially expressed genes with high variability in expression levels across all samples. For biological data, the success of predictor genes identified in appropriately classifying an independent sample is reported.</p
Atypical Balance between Occipital and Fronto-Parietal Activation for Visual Shape Extraction in Dyslexia
Reading requires the extraction of letter shapes from a complex background of text, and an impairment in visual shape extraction would cause difficulty in reading. To investigate the neural mechanisms of visual shape extraction in dyslexia, we used functional magnetic resonance imaging (fMRI) to examine brain activation while adults with or without dyslexia responded to the change of an arrow’s direction in a complex, relative to a simple, visual background. In comparison to adults with typical reading ability, adults with dyslexia exhibited opposite patterns of atypical activation: decreased activation in occipital visual areas associated with visual perception, and increased activation in frontal and parietal regions associated with visual attention. These findings indicate that dyslexia involves atypical brain organization for fundamental processes of visual shape extraction even when reading is not involved. Overengagement in higher-order association cortices, required to compensate for underengagment in lower-order visual cortices, may result in competition for top-down attentional resources helpful for fluent reading.Ellison Medical FoundationMartin Richmond Memorial FundNational Institutes of Health (U.S.). (Grant UL1RR025758)National Institutes of Health (U.S.). (Grant F32EY014750-01)MIT Class of 1976 (Funds for Dyslexia Research
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